Automated Phenotyping of Faba Bean Seeds Using Segment Anything 2 for Trait Extraction

This capsule implements a fully automated, training-free workflow for extracting phenotypic traits from bean seed images. The pipeline uses the pretrained Segment Anything Model (SAM2.1, Meta AI) to perform high-precision instance segmentation without manual prompts or annotated training data, followed by custom post-processing for trait quantification. The workflow extracts calibrated morphological features (size, shape, and spatial measurements) from binary seed masks using a reference coin and performs colorimetric analysis using a 24-patch color card to characterize dominant seed coat color. Thousand grain weight (TGW, g) is also included in the pipeline. For computational efficiency, the capsule demonstrates the complete pipeline using a small representative subset of images. Full-scale analyses reported in the manuscript were conducted using the same workflow.